TY - JOUR
T1 - Hash-based early recognition of gesture patterns
AU - Ko, Yoshiyasu
AU - Shimada, Atsushi
AU - Nagahara, Hajime
AU - Taniguchi, Rin ichiro
N1 - Funding Information:
This work was supported by KAKENHI Grant-in-Aid for Young Scientists (A) (23680018).
PY - 2013/2
Y1 - 2013/2
N2 - In these days, "early recognition" of gesture patterns has been studied by many researchers. Early recognition is a method to make a decision of gesture recognition at the beginning part of it. In traditional method, the key postures for a gesture are utilized for recognition and early recognition is performed frame-by-frame. However, this method has a problem that computational time in recognition processing increases in proportion to size of posture database. If the processing time becomes longer, some input frames will be ignored from the processing. It results in lower recognition accuracy. In this paper, we introduce a hash-based approach to search the posture database. It realizes real-time processing, and keep high performance of recognition.
AB - In these days, "early recognition" of gesture patterns has been studied by many researchers. Early recognition is a method to make a decision of gesture recognition at the beginning part of it. In traditional method, the key postures for a gesture are utilized for recognition and early recognition is performed frame-by-frame. However, this method has a problem that computational time in recognition processing increases in proportion to size of posture database. If the processing time becomes longer, some input frames will be ignored from the processing. It results in lower recognition accuracy. In this paper, we introduce a hash-based approach to search the posture database. It realizes real-time processing, and keep high performance of recognition.
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U2 - 10.1007/s10015-012-0085-6
DO - 10.1007/s10015-012-0085-6
M3 - Article
AN - SCOPUS:84874206716
SN - 1433-5298
VL - 17
SP - 476
EP - 482
JO - Artificial Life and Robotics
JF - Artificial Life and Robotics
IS - 3-4
ER -